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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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2
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Thesis -
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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4
Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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6
Modification of the CREAMS Nutrient submodel
Published 2011“…The CREAMS nutrient submodel was modified to improve the prediction, of the nitrogen loss from a flat agricultural field with a fluctuating water table.The CREAMS nutrient submodal was modified by incorporating a water function in the CREAMS denitrification algorithm.The capability of the CREAMS nutrient submodel and modified CREAMS nutrient submodel in predicting nitrogen loss was evaluated by using linear regression analysis, t-test on the slope and intercept of the regression equation, standard deviation of differences, absolute average differences, and percent error.Observed data from an experimental plot near Baton Rouge, Louisiana, USA were used in this study.The modified model underestimated the total nitrogen losses by 2% compared to 35% overestimation by the CREAMS model.Overall performance of the modified model in predicting nitrogen losses was satisfactory.…”
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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8
Parametric modelling of twin rotor system using chaotic fractal search algorithm
Published 2016“…Then, the modified Fractal Search algorithms are employed to optimise the parameters for an ARX model of twin rotor system in hovering mode. …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
Published 2012“…Keywords: Autoregressive Model Algorithm (ARMA), Magnetic Resonance Imaging (MRI), Reconstruction …”
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Monograph -
12
System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Comparison of dose calculation algorithms model: convolution, superposition, and fast superposition in 3-D Conformal Radiotherapy (3D-CRT) treatment plan
Published 2019“…In conclusion, the evaluation of radiotherapy treatment plan shall take into account the type of dose calculation algorithm model in order to optimize radiotherapy treatment and ensure the radiation safety to the patient.…”
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Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting
Published 2020“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of three main phases; data pre-processing, forecasting based on WeSuSFTS model and model evaluation. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking
Published 2018“…The simulation work covers modelling of the photovoltaic module, and the boost DC-DC converter and power LED light as a load, with maximum power point tracking algorithm to form a photovoltaic system. …”
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Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity
Published 2016“…However, the NLFXLMS is limited by two practical issues such that the degree of nonlinearity has to be known in advance and the SEF cannot be evaluated in real time. In this work, the NLFXLMS algorithm is modified by incorporating the tangential hyperbolic function (THF) to model the saturation effect of the loudspeaker. …”
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Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods
Published 2023“…Evaluation of the XGB regression and DTR performance shows that the developed ML models outperform the RSM in predicting the MSCR rutting parameters.…”
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Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing
Published 2017“…The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.…”
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